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@caseywatts
caseywatts / README.md
Last active October 19, 2026 21:32
USWDS-themed Instantsearchjs (Algolia search / Meillisearch)
@eliottness
eliottness / README.md
Last active October 19, 2026 21:18
Bitwarden SSH agent in WSL2 via a systemd user service (socat + npiperelay) — with the gotchas that make ssh-add hang

Bitwarden SSH agent in WSL2 (via systemd)

Use the SSH keys stored in your Windows Bitwarden Desktop vault from inside WSL2 — ssh, git, ssh-add, etc. — managed by a systemd user service instead of a fragile .zshrc snippet.

This bridges the Windows OpenSSH-agent named pipe that Bitwarden exposes (\\.\pipe\openssh-ssh-agent) to a Unix socket inside WSL using npiperelay + socat.

@tykurtz
tykurtz / grokking_to_leetcode.md
Last active October 19, 2026 21:13
Grokking the coding interview equivalent leetcode problems

GROKKING NOTES

I liked the way Grokking the coding interview organized problems into learnable patterns. However, the course is expensive and the majority of the time the problems are copy-pasted from leetcode. As the explanations on leetcode are usually just as good, the course really boils down to being a glorified curated list of leetcode problems.

So below I made a list of leetcode problems that are as close to grokking problems as possible.

Pattern: Sliding Window

@karpathy
karpathy / microgpt.py
Last active October 19, 2026 21:12
microgpt
"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.
@karpathy
"""
import os # os.path.exists
import math # math.log, math.exp
@veekaybee
veekaybee / normcore-llm.md
Last active October 19, 2026 21:10
Normcore LLM Reads

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Screenshot 2023-12-18 at 10 40 27 PM

Pre-Transformer Models

Volt Individual Contributor License Agreement ("CLA")

Thank you for your interest in contributing to Volt!

In order to clarify the intellectual property rights in any contributions of code or documentation, we require contributors to accept this Contributor License Agreement ("CLA").


1. Definitions

  • "You" (or "Contributor") means the individual copyright owner or legal entity submitting the Contribution.
  • "Volt" means the Volt Digital Audio Workstation project, its associated code repositories and organizations (founded and led by TheRedXD, known on GitHub as @TheRedXD / Matthew), and any designated successor organization, cooperative, or legal entity established to steward the project.

MaximumADHD's "Smooth-Flow" Luau Style

Smooth-Flow is my nitpicky Luau coding style that encases various patterns that I've observed with how I've gone about writing and cleaning up Luau code over the past few years.

It is 99% compatible with StyLua and Roblox's Lua style guide, it just introduces some additional nitpicking and aesthetic changes to help with the readability and overall presentability of the Luau code.

Style Goals

  • Write code that groups related actions and assignments.
  • Produce aesthetically consistent code through simple rules.

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@Jimgitsit
Jimgitsit / team-wiki-spec.md
Last active October 19, 2026 21:04
Team Wiki — a specification for a centralized, agent-maintained wiki on S3 + a Lambda MCP server. Hand it to an agent to get it set up.

Team Wiki — a specification for a centralized, agent-maintained wiki on S3 + a Lambda MCP server. Hand it to an agent to get it set up.

Team Wiki — Specification

A shared knowledge base your agents write and maintain themselves — plain markdown in S3, reached through an MCP server.

Features

  • Autonomous: Agents use it and maintain it automatically. Knowledge of it is loaded in every session (in CLAUDE.md).